How can I make time series plot?-CodePudding

I created a dataset with these variables. But Date variable should be the first 128 day of the year. My problems are:

I could not convert the Date variable.
How can I plot wheat, hazelnut and corn in time?
How can I make subplot by repeating the previous plot with only two months data?

Can you help me please.

a <- 1
b <- 3
c <- 0

Date <- c(1:128)
Wheat <- rnorm(128, mean = a, sd = b)
Hazelnut <- runif(128, a ,b)
Corn <- rnorm(128, mean = c, sd = b)

df <- as.data.frame(cbind(Date, Wheat, Hazelnut, Corn))
df$Date <- as.Date(df$Date)

CodePudding user response：

How about this:

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
library(tidyr)
a <- 1
b <- 3
c <- 0
Date <- seq(ymd("2022-01-01"), ymd("2022-01-01") 127, by=1)
Wheat <- rnorm(128, mean = a, sd = b)
Hazelnut <- runif(128, a ,b)
Corn <- rnorm(128, mean = c, sd = b)

df <- data.frame(Date=Date, 
                    Wheat=Wheat, 
                    Hazelnut=Hazelnut, 
                    Corn=Corn)

df <- df %>% 
  pivot_longer(c("Wheat", "Hazelnut", "Corn"), 
               names_to="crop",
               values_to="vals")


ggplot(df, aes(x=Date, y=vals))   
  geom_line()   
  facet_wrap(~crop, ncol=1)   
  theme_classic()

df %>% filter(Date <= ymd("2022-02-28")) %>% 
ggplot(aes(x=Date, y=vals))   
  geom_line()   
  facet_wrap(~crop, ncol=1)   
  theme_classic()

^{Created on 2022-04-19 by the}

To create the plot only for two months, just subset the data in the code above, e.g.

matplot(dat[dat$Date < as.Date('2022-03-01'), -1], ...)

In case you want to create an actual time-series object, use ts,

(df_ts <- ts(with(df, data.frame(Wheat, Hazelnut, Corn)), frequency=365,
             start=2022))
# Time Series:
# Start = c(2022, 1) 
# End = c(2022, 128) 
# Frequency = 365 
# Wheat Hazelnut        Corn
# 2022.000  5.11287534 1.220670  0.75783511
# 2022.003 -0.69409451 2.079597 -3.88200740
# 2022.005  2.08938523 2.142468 -2.87751133
# 2022.008  2.89858781 2.237903  3.25732456
# [...]
# 2022.340  0.99453216 2.162396 -2.35466343
# 2022.342 -0.28477664 1.940185  0.49024896
# 2022.345 -0.84101482 1.730028 -3.71014271
# 2022.348 -5.07403354 1.560249  3.13762133

where

class(df_ts)
# [1] "mts"    "ts"     "matrix"

and plot it.

plot(df_ts)